System and method for railway right-of-way occupancy detection

ABSTRACT

A rail crossing occupancy detection system and method includes a plurality of LIDAR sensors operable to detect objects in one or more areas of interest within a field of interest, such as the areas including and surrounding a rail crossing, station, platform, or other railway right-of-way area. The field of interest is divided into one or more areas of interest, with one or more LIDAR sensors positioned to detect the presence of one or more objects within each of the one or more areas and to provide alerts based on the detection and behavior of the objects such as movement or other parameters associated with the objects.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims the benefit of U.S. Provisional PatentApplication No. 63/367,938, filed Jul. 8, 2022, the disclosure of whichis hereby incorporated herein in its entirety by reference.

FIELD

The present invention relates generally to the field of railroads, andmore particularly to a system and method for detecting trains, vehicles,people, or other objects within a railway right-of-way region, detectingand calculating parameters associated with the detected objects, andproviding alerts and/or control signals based on the detected objectsand their associated parameters.

BACKGROUND

Systems and methods of detecting the presence or absence of objects areknown in the art, and such detection has been applied to the field ofrailroads. For example, U.S. Pat. No. 9,376,129 discloses the use ofRADAR sensors to detect a blocked rail crossing by detecting thepresence or absence of an object in the crossing area. Similar detectionof the presence or absence of objects in an area has been used in thefield of trespasser detection (i.e., detection of the presence of anunexpected object in an area) and in the field of traffic counting(i.e., detection and counting of the presence of vehicles or people in aparticular area).

While such systems and methods are useful, they are also rudimentary,typically only detecting the presence or absence of an object in adefined area and taking a particular action in response—e.g., keeping arunning tally of objects entering the defined area (i.e., trafficcounting), or generating an alert or signal indicating the presence orabsence of an object in the defined area (i.e., blocked rail crossingdetection).

Thus, it can be seen that there remains a need in the art for animproved system and method for detecting and monitoring objects in arail crossing area and providing responses tailored to the detectedobject or objects.

SUMMARY

Embodiments of the invention are defined by the claims below, not thissummary. A high-level overview of various aspects of the invention areprovided here for that reason, to provide an overview of the disclosure,and to introduce a selection of concepts that are further described inthe detailed description section below. This summary is not intended toidentify key features or essential features of the claimed subjectmatter, nor is it intended to be used as an aid in isolation todetermine the scope of the claimed subject matter. In brief, thisdisclosure describes, among other things, a system and method fordetecting objects in a rail crossing area and providing outputs,actions, and responses based on the detected objects and parameters andinformation associated with the detected objects.

In one embodiment, a rail crossing occupancy detection system and methodincludes a plurality of LIDAR sensors positioned and operable to detectobjects in one or more areas of a field of interest (FOI) beingmonitored, such as the region including and surrounding a rail crossing.The region is divided into one or more areas of interest (AOI), with oneor more LIDAR sensors positioned to detect the presence of one or moreobjects within each of the one or more areas. For example, the regionbeing monitored may be a rail crossing area, with multiple areas withinthat region monitored, such as the rail track, the crossing gates, andthe roadway within, and outside of, the crossing gates. Thus, while thesystem monitors the entire rail crossing region, that region issubdivided into multiple areas, each of which includes one or more LIDARsensors associated with that area for detecting objects and parametersand information associated with the objects.

In one aspect, the plurality of LIDAR sensors are connected andintegrated into an object detection subsystem which includes logic andcontrol circuitry to communicate with and receive data from each of thesensors. The logic and control circuitry may include processors, memory,and power supply circuitry, and is configured to define various regionsand areas of coverage by various combinations of the LIDAR sensors. Inanother aspect, the object detection subsystem generatesthree-dimensional object location data for each detected object-such astrains, crossing gates, vehicles, people, and other objects-from imagedata captured by the LIDAR sensors.

In a further aspect, the system and method of the present inventionderives one or more parameters and/or information associated withdetected objects, such as an object's speed, direction of movement, andsize, i.e., objects of interest (OOI) and behaviors of interest (BOI).Thus, both static and moving objects may be detected, and moving objectsmay be tracked as they traverse through the rail crossing area orthrough one or more areas of the region.

In another aspect, the occupancy system and method may be deployed inany railway right-of-way region or area, such as at-grade crossings,stations, platforms, bridges, tunnels, trespasser problem areas, or anyother area within or near a railway right-of way in which monitoring forobjects of interest and/or behaviors of interest is required or desired.

In further embodiments, the type of object is identified by comparisonof the parameters and information associated with the object to adatabase of known objects and parameters. For example, a train may beidentified by its size, its position above and along the tracks within aregion, and by its direction of travel within the area. Similarly,vehicles, people, and other objects may be identified by comparing theirphysical size and features (speed, movement patterns, etc.) with adatabase of known objects and their associated parameters.

In various embodiments, the system and method for rail crossingoccupancy detection can be employed for train detection, gatemalfunction detection, vehicle intrusion detection, object detection,near miss detection, train/object collision detection, loiteringdetection, suspicious object detection, and detection of other objectsand events.

DESCRIPTION OF THE DRAWINGS

Illustrative embodiments of the invention are described in detail belowwith reference to the attached drawing figures, and wherein:

FIG. 1 is a top plan view of a system in accordance with an exemplaryembodiment of the present invention deployed in a rail crossing region.

FIG. 2 is a schematic block diagram of a system in accordance with anexemplary embodiment of the present invention.

FIG. 3 is a flow diagram of a method of train detection in accordancewith an exemplary embodiment of the present invention.

FIG. 4 is a flow diagram of a method of gate malfunction detection inaccordance with an exemplary embodiment of the present invention.

FIG. 5 is a flow diagram of a method of detecting vehicle incursion intothe railway in accordance with an exemplary embodiment of the presentinvention.

FIGS. 6A, 6B, 6C, and 6D depict areas and objects within a railwaycrossing region in a vehicle incursion detection scenario as alsodescribed with respect to FIG. 5 .

FIG. 7 is a flow diagram of a method of detecting an object entering arail track in accordance with an exemplary embodiment of the presentinvention.

FIG. 8 is a flow diagram of a method of detecting a near miss inaccordance with an exemplary embodiment of the present invention.

FIG. 9 is a flow diagram of a method of detecting a train/objectcollision in accordance with an exemplary embodiment of the presentinvention.

FIG. 10 is a flow diagram of a method loitering detection in accordancewith an exemplary embodiment of the present invention.

FIG. 11 is a flow diagram of a method of suspicious object detection inaccordance with an exemplary embodiment of the present invention.

FIGS. 12A, 12B, and 12C depict areas and objects within a railwaycrossing region in a train in crossing region without gates loweredscenario.

DETAILED DESCRIPTION

As required, detailed embodiments of the present invention are disclosedherein; however, it is to be understood that the disclosed embodimentsare merely exemplary of the invention, which may be embodied in variousforms. Therefore, specific structural and functional details disclosedherein are not to be interpreted as limiting, but merely as a basis forthe claims and as a representative basis for teaching one skilled in theart to variously employ the present invention in virtually anyappropriately detailed structure.

The present invention is directed to a system and method for railcrossing occupancy detection. Looking first to FIGS. 1 and 2 , anexemplary embodiment of the system of the present invention is depicted.As seen in FIG. 1 , a plurality of LIDAR sensors L1 through L7 arepositioned around a region of interest 98, a rail crossing. As seen inthe figure, the rail crossing comprises a railway 20 extending across aroadway 21 to allow a train to pass over the roadway. The railwayincludes two rails 22 supported by a plurality of ties 24. Crossinggates 26 a, 26 b, 26 c, and 26 d raise and lower to block and unblockthe roadway 21 to prevent vehicles from entering the railway when atrain is approaching and/or to act as a visual indication that a trainis approaching or is present on the railway. It should be understoodthat in alternative embodiments that other signals, such as warninglights and the like, may be employed in addition to, or in place of, thecrossing gates. It should be further understood that otherconfigurations of crossing gates, such as single gates on each side ofthe railway, are within the scope of the present invention.

LIDAR sensors L1 through L7 are operable to detect objects within theirrespective fields of view and, as depicted in FIG. 2 , are connected tologic and control circuitry to form an object detection subsystem 100.Looking to FIG. 2 , the object detection subsystem 100 includes logicand control circuitry 102 comprised of one or more processors 104,memory 106, database 108 and control logic 110.

In the exemplary embodiment as depicted in FIG. 2 , the output of theobject detection subsystem 100 is used to control and/or signal variousdevices, such as signage 111 a, alert devices 111 b such as audio orvisual alerts, reports 111 c, crossing signals 111 d, and crossing gates111 e based on logical and algorithmic programming in the control logic110. In alternative embodiments, the output of the object detectionsubsystem 100 may be directed to an external computer or controllerwhich includes its own control logic to determine actions to take anddevices to control in response to data provided by the object detectionsubsystem 100.

Looking back to FIG. 1 , LIDAR sensors L1 through L7 are positioned suchthat their fields of view encompass the entire field of interest (FOI),in this case the railway crossing region. Within the field of interest,various areas of interest are defined in which the detection of objectsis desired. For example, in FIG. 1 , area 112 is an area of the roadwayoutside of the first and second crossing gates 26 a, 26 b, area 114 isthe area surrounding and including the first crossing gate 26 a, area116 is the area surrounding and including the second crossing age 26 b,area 118 is the area of the railway 20 crossing the roadway 21, area 120is the area surrounding and including the third crossing gate 26 c, area122 is the area surrounding the fourth crossing gate 26 d, and area 124is the area of the roadway outside of the third and fourth crossinggates. Track zones, or areas 126, 128, located on either side of thecrossing zone, allow detection of a train (or other object) travellingalong the railway into or away from the crossing zone.

It should be understood that the areas 112, 114, 116, 118, 120, 122,124, 126, and 128 as just described are virtual areas corresponding tothe areas of interest within the field of interest, and that there isnot necessarily a one-to-one correspondence between the field of view ofa particular LIDAR sensor and an area of interest. For example, areas112, 114, and 116 are all within the field of view of LIDAR sensor L1,and thus a single LIDAR sensor may be employed to cover and detectobjects within all of those areas. Or, as seen in FIG. 1 , LIDAR sensorL2 may encompass only area 112 within its field of view. Regardless ofthe number of LIDAR sensors used, the logic and control circuitry withinthe object detection subsystem will virtually mesh all of the separateLIDAR signals, accounting for overlap as necessary, with the variousseparate areas of interest defined as logical subsets within the entireLIDAR viewing profile.

Thus, the LIDAR sensors are preferably positioned to cover the entirefield of interest, with the various areas of interest defined withinthat field of interest regardless of which physical LIDAR sensor (orsensors) include that area within its field of view.

With the LIDAR sensors positioned to cover the field of interest and thelogic and control circuitry of the object detection subsystem incommunication with the LIDAR sensors, objects within any of the areas,and movement or motion of objects within the areas can be detected andvarious occupancy detection scenarios can be implemented as will now bedescribed.

The system and structure as just described can detect objects andconditions by monitoring specific areas of interest within a field ofinterest and iteratively track the state of objects within those areasand determine what has changed since the last iteration. In variousembodiments, the system and method for rail crossing occupancy detectioncan be employed for train detection, gate malfunction detection, vehicleintrusion detection, object detection, near miss detection, train/objectcollision detection, loitering detection, suspicious object detection,and detection of other objects and events as will now be described.

Train Detection

In one exemplary embodiment, the system and method of the presentinvention may be configured to detect a train traveling along a railwayby tracking the state of objects within three defined areas-for example,with reference to FIG. 1 , track zones 126, 128, and crossing zone 118are monitored by the LIDAR detectors in the manner as previouslydescribed to detect a train (or other object) travelling along therailway 20.

A method of detecting a train travelling in those zones is depictedgenerally as numeral 240 in FIG. 3 . Looking to FIG. 3 in conjunctionwith FIG. 1 , to detect a train (or other object) travelling along arailway, the system as previously described is first initialized, withthe region of interest defined and the appropriate LIDAR sensorscovering the area(s) within the region of interest monitored by theobject detection subsystem 100. The system iteratively cycles thoroughthe covered areas (the track zones 126, 128 and crossing zone 118) todetect whether an object, or a change in state of a previously detectedobject, has occurred, with detection of train accomplished byimplementing the following logic.

At block 242, upon detection of an object within the region of interest,the system uniquely identifies the object by identifying features andparameters associated with the object, such as the size of the object,the shape of the object, the position of the object, the velocity of theobject (if moving), and other parameters associated with the object. Atblock 244, based on the detected object and its parameters, the systemdetermines and classifies the object as a train. At bock 246, if thedetection of the train within the region is the first detection (i.e.,the system had not, on previous iterations, identified a train withinthe region), then at block 248 the system sends a notification alertthat a train has entered the region and sets an internal state parameternoting that a train has been detected entering the region—with the stateparameter of “entering” used on subsequent iterations of the logic totrack further movement of the train. It should be understood thatdetection of a train entering from either side of the crossing may beaccomplished, for example a train entering either of zone 126 or 128 maybe detected, with the object detection subsystem and logic and controlcircuitry operable to distinguish between the two and to furtherdetermine the direction in which the train is travelling based on whichzone it enters first.

If, at block 246, the system has already initially detected a trainentering the region as just described (i.e., the state parameter is setto “entering”), at block 250 the system continues to monitor the areasof the region of interest to determine movement of the detected trainbeyond the “entering” status and to detect any transition of the trainwithin the region of interest.

It should be understood, as noted above, that the logic implemented bythe object detection subsystem is iterative, and that multiple samplesper second may be captured by the logic and control circuitry so thatmovement of an object (such as a train) may be initially detected,tracked as the object traverses across the various monitored areaswithin the region of interest, and detected as the object eventuallyleaves the region, with the “state” parameter providing one or morestates of the object/train within the region.

For example, as just described, the system may detect a train enteringthe region (e.g., the system initially had no detection of a train, thena train enters the region and the state changes to “entering”), maytrack as the train continues to occupy the region (e.g., a train maytake seconds or minutes to travel through the crossing area), and maytrack and detect as the train prepares to leave the region (e.g., thetrain has traversed the region but is still detected in the final areaof the region), and may detect that the train has exited the region(e.g., no train is detected within any area of the region). Thisiterative monitoring and state determination allows for complexscenarios implemented by the object detection subsystem and logic andcontrol circuitry to monitor movement of a train within the monitoredregion beyond a simple “object present” and “object not present”detection as in the prior art.

It should be further understood that the iterative monitoring of thepresent invention allows calculation of additional parameters associatedwith the object/train— for example, velocity, direction, andacceleration may be calculated based on the iterative parameters sampledby the object detection subsystem.

Looking still to FIG. 3 , at block 250, the system detects the traintransitioning to an area within the region of interest beyond the zonein which the train entered. For example, with reference to FIG. 1 , atrain entering the region at zone 126 will transition to zone 118 andthen to zone 128. Thus, once the train is detected transitioning fromzone 126 to zone 118, at block 212 the system determines that if theprevious state was “entering” then at block 254 the state of the systemis set to “occupying” and an alert of that event is sent.

If, at block 252, the previous state of the system was “occupying”(i.e., the system had previously detected a train occupying the region,then at block 256, upon detection of the train transitioning to thefinal area within the region (e.g., referring to FIG. 1 , the train haspreviously moved from zone 126 to zone 118, and now moves to zone 128)at block 258 the system sets the state to “exiting” and sends an alertof that event.

Once a detection occurs and/or a state is set as described above, thelogic is iteratively repeated, with subsequent changes in the state ofdetection of the train/object updated as described above.

Thus, it can be seen that the object detection subsystem and logic andcontrol circuitry can monitor a region of interest and detect theinitial entry of a train (or other object) into the region, track thetrain as it continues to occupy the region, and detect when the trainleaves the region. It should be understood that the detection as justdescribed is exemplary, and that other detection scenarios having moreor fewer areas within a region may be implemented by the system of thepresent invention.

It should be further understood that the object detection subsystem andlogic and control circuitry may include error detection capabilities toalert a user of an anomaly or potential malfunction. For example, in thescenario as just described, if the current state of the system is “none”(i.e., no train or object currently detected) and the system detects atrain or object in zone 118, without ever having detected a train“entering” the region through zone 126, that anomaly may be flagged andreported to an operator. Similarly, any other variances or logicalanomalies may be detected and reported.

Gate Malfunction Detection

Looking to FIG. 4 in conjunction with FIG. 1 , in another exemplaryembodiment, the system and method of the present invention are deployedto detect a malfunction of a crossing gate. In this exemplaryembodiment, the system is configured to monitor the position of crossinggates within the region of interest, for example, zones 114, 116, 120,and 122 are monitored to detect the position and/or movement of crossinggates 26 a, 26 b, 26 c, and 26 d, respectively, with the train“entering”, “occupying”, and “exiting” states also operating asdescribed above with respect to the train detection scenario.

The logic flow is depicted generally in FIG. 4 as numeral 260. At block261, if the state of the gate detection is “none” (i.e., no gates haveyet been identified classified), then at 262, the system initiallydetects an object (i.e., the gate) in each of the areas within theregion, that is, the gates 26 a, 26 b, 26 c, and 26 d. At block 264, thesystem classifies the detected object in each region as a gate, and thuswill subsequently track the position and/or movement of each gate.

With the gates identified, the iterative logic continues to monitor theposition and movement of the identified gates, and detects various gatemalfunction scenarios: a crossing gates do not lower scenario in blocks266, 268, and 270; a crossing gates do not raise scenario in blocks 272,274, and 276; and a crossing gates lower unexpectedly scenario in blocks278 and 280 as will now be described.

To detect a crossing gates do not lower malfunction, at block 266, thesystem first determines that a train has been detected within the regionof interest (as described above, a train entering, occupying, or exitingthe region is a detected train within the region). At block 268, thesystem determines, based on parameters iteratively monitored for eachidentified gate, whether any of the gates did not move to the completelylowered position withing a predetermined amount of time. If so, at block270, the system sends a gate malfunction alert identifying the gate(s)at issue. Thus, the system can not only detect and report that a gatedid not lower at all, but can also detect and report that a gate loweredtoo slowly.

To detect a crossing gates do not raise malfunction, at block 272, thesystem first determines that a train has been detected within the regionof interest (as described above). At block 274, the system determines,based on parameters iteratively monitored for each identified gate,whether any of the gates did not move to the completely raised positionwithing a predetermined amount of time. If so, at block 276, the systemsends a gate malfunction alert identifying the gate(s) at issue. Thus,the system can not only detect and report that a gate did not raise atall, but can also detect and report that a gate raised too slowly.

To detect a crossing gates lowers unexpectedly malfunction, at block278, the system first that a train has not been detected within theregion of interest (as described above) and further detects that anidentified gate is in the lowered position (or alternatively, is not inthe completely raised position). At block 280, they system sends a gatemalfunction alert identifying the gate(s) at issue.

Vehicle Turning onto Rail Detection

Turning to FIG. 5 , in conjunction with FIG. 1 , in another exemplaryembodiment, the system and method of the present invention are used todetect a vehicle (or other non-train object) turning onto the railtrack. As seen in FIG. 1 , various zones or areas within the entireregion of interest 98 are defined, with several zones (126, 118, and 128associated with the railway 20) and other zones (112, 118, and 124associated with the roadway 21), with zone 118 encompassing both therailway 20 and the roadway 21.

The logic flow for the detection is depicted in FIG. 5 generally asnumeral 350. At block 352, with an initial state of an objectundetected, the system detects and identifies an object within theregion. At block 354, the system classifies the detected object as a“non-train” object, thus any car, motorcycle, or other non-train objectmay be detected. At block 356, the system detects that the non-trainobject is within any area in which only trains would be expected, forexample, zones 126 and 128 of FIG. 1 , which are zoned on the railway20. Upon detection of an object in these zones, the system sets a stateparameter to “object”, and at block 362 the system sends an alert of thedetected non-train object on the railway.

At block 358, as the logic iterates the system keeps track of the amountof time in which the object remains in the region of interest. If theobject remains longer than a predetermined allowable time, then at block368 the system sends an alert of the persistence of the object withinthe region.

Preferably, the system sends an alert specific to the type of objectdetected, such as a vehicle, pedestrian, box, etc. so that a user mayrespond appropriately to the detection and alert.

With the logic and detection scenarios set forth, FIGS. 6A, 6B, 6C, and6D depict the various scenarios as just described with respect to thelogic flow diagram of FIG. 5 in which the system and method of thepresent invention detect that a vehicle is present between closedcrossing gates. An alert and/or other action would be generated inresponse to such detection.

Looking to FIG. 6A, a railway crossing region—the field of interest inthis scenario-is depicted generally as numeral 200. The railway crossingregion includes a roadway 202 allowing vehicles to cross the rail track204, with crossing gates 206 a, 206 b, 206 c, 206 d positioned on eachside of the roadway 202, the crossing gates normally operable toclose/lower when a train is approaching the crossing region to detervehicles from entering the crossing region and to raise when the trainhas sufficiently cleared the crossing region. Signal/warning lights areincluded with each crossing gate mechanism to provide a visualindication of the presence or approach of a train.

Looking to FIG. 6B, an area 208 is defined by the system to detectobjects in the area where the rail track 204 crosses the road 202. Thus,as depicted, a vehicle 210 has entered that area 208 and is detected bythe system. As can also be seen in FIG. 6B, the crossing gates are eachdetected within an area corresponding to each gate, with the systemdetecting that all of the crossing gates are in the lowered/closedposition. Thus, the system determines that a vehicle has entered thecrossing area with all gates, down, thus the vehicle 210 is between theclosed/lowered crossing gates.

Looking to FIG. 6C, the system detects that the vehicle has entered thearea 212 defining the rail track crossing the roadway—i.e., that thevehicle between the gates has moved from the roadway on one side of thetrack and onto the track.

And, looking to FIG. 6D, the system detects that the vehicle 210 hasentered area 214, i.e., the roadway area on the opposite side of thetrack, indicating that the vehicle has crossed the track. As also seenin FIG. 6D, the system can provide a signal to allow the crossing gateto raise to allow the vehicle 210 to exit from the area.

The system would likewise generate an alert, signal or other alarm tonotify of the vehicle incursion and positioning between the loweredgates.

As described, the system and method of the present invention may beconfigured to detect and alert to various other scenarios, several ofwhich will now be described with respect to FIGS. 7, 8, 9, 10, and 11 .

Object Entering Track Detection

Looking to FIG. 7 , in another exemplary embodiment, the system andmethod of the present invention are used to detect an object enteringthe track. At block 400, the system detects and identifies an objectwithin the region of interest. At block 402, the system determines thatthe object is not a train, and at block 404 the system detects that theobject is within a zone, area, or region associated with railway track.Finally, at block 406, the system sends an alert of the object detectedentering the track.

In further embodiments, the system may further determine if the objectis a train, a vehicle, a cyclist, a pedestrian, or other object andprovides an appropriate alert. And in further embodiments, the objectdetection system may provide two-dimensional map coordinates of thedetected object, or two-dimensional projection coordinates.

Near Miss Detection

Turning to FIG. 8 , in another exemplary embodiment, the system andmethod of the present invention are used to detect a near misscondition. To detect a near miss, the system generally detects that atrain is present and that an object is located within a predetermineddistance threshold from the detected train, and provides an alert.

At block 410, the system detects and identifies an object entering aregion of interest. At block 412, the system classifies the detectedobject, and at block 414, the system detects the object exiting theregion of interest. At bock 416, the system detects a train within theregion of interest within a predetermined amount of time from the timethe detected object exited the region of interest. At block 420, thesystem sends a near miss alert to a user.

In further embodiments, the system further determines if the object is atrain, a vehicle, a cyclist, a pedestrian, or other object and providesan appropriate alert. And in further embodiments, the object detectionsystem provides two-dimensional map coordinates of the detected object,or two-dimensional projection coordinates.

Train/Object Collision Detection

Turning to FIG. 9 , in another exemplary embodiment, the system andmethod of the present invention are used to detect a collision between atrain and an object. To detect a train/object collision, the systemgenerally detects that a train is present (as described previously) andthat a detected object is within the area occupied, or zone extents, ofthe train, and provides an alert.

At block 430, the system detects and identifies an object entering aregion of interest. At block 432, the system classifies the detectedobject. At block 434, the system detects a train entering a zoneassociated with the railway track in the region of interest while thedetected object is still within that zone. Finally, at block 436, thesystem sends a train/object collision alert.

In further embodiments, the system further determines if the object is atrain, a vehicle, a cyclist, a pedestrian, or other object and providesan appropriate alert. And in further embodiments, the object detectionsystem provides two-dimensional map coordinates of the detected object,or two-dimensional projection coordinates.

Loitering Detection

Looking to FIG. 10 , in another exemplary embodiment, the system andmethod of the present invention are used to detect loitering within thefield of interest.

To detect loitering within a field of interest, the system generallydetects that the discrete average speed of one or more objects withinthe field of interest over a predetermined time period is less than apredetermined set speed threshold, and provides an alert.

At block 440, the system detects and identifies an object within aregion of interest. At block 442, the system classifies the object as aperson. At block 444, the system determines whether the detected personhas remained in the region of interest (or a zone within the region ofinterest) for longer than a predetermined amount of time. At block 446,the system sends a loitering alert to a user.

And in further embodiments, the object detection system providestwo-dimensional map coordinates of the detected person, ortwo-dimensional projection coordinates.

Suspicious Object Detection

Turning to FIG. 11 , the system and method of the present invention areused to detect suspicious objects within the field of interest.

To detect a suspicious object within a field of interest, the systemgenerally detects that the discrete average speed of an object withinthe field of interest over a predetermined time period is less than apredetermined set speed threshold, and determines that the physicaldimensions of the detected object are consistent with a suspiciousobject.

At block 450, the system detects and identifies an object within aregion of interest. At block 452, the system classifies the object as anon-train, non-person object based on detected physical characteristicsof the object. At block 454, the system determines whether the detectedobject has remained within the region of interest for longer than apredetermined time, and at block 456, the system sends a suspiciousobject alert to a user.

In further embodiments, the system further determines if the object is atrain, a vehicle, a cyclist, a pedestrian, or other object and providesan appropriate alert. And in further embodiments, the object detectionsystem provides two-dimensional map coordinates of the detected object,or two-dimensional projection coordinates.

Finally, FIGS. 12A, 12B, and 12C depict a scenario in which the systemand method of the present invention detect that a train is present onthe railway while one or more of the crossing gates are not lowered. Analert and/or other action would be generated in response to suchdetection.

Looking to FIG. 12A, a railway crossing region is depicted generally asnumeral 300. The railway crossing region includes a roadway 302 allowingvehicles to cross the rail track 304, with crossing gates 306 a, 306 b,306 c, 306 d positioned on each side of the rail track 304, the crossinggates normally operable to close/lower when a train is approaching thecrossing region to deter vehicles from entering the crossing region andto raise when the train has sufficiently cleared the crossing region.Signal/warning lights are included with each crossing gate mechanism toprovide a visual indication of the presence or approach of a train.

Looking to FIG. 12B, a first area 308 is defined by the system to detectobjects in the area where the rail track 304 crosses the road 302. Thus,as depicted, a train 310 entering that first area 308 is detected by oneor more LIDAR sensors defining that first area. In other embodiments,objects other than a train may likewise be detected, such as a surveyvehicle, repair equipment, and the like.

Second, third, fourth, and fifth areas 312, 313, 314, 315 are defined toencompass each of the crossing gates and to detect the position of eachof the gates. As seen in the depicted scenario of FIG. 12B, a train isentering the rail track crossing the road (and thus is detected in area308). At the same time, the system detects that all of the crossinggates—as detected in areas 312, 313, 314, and 315—are in theup/not-lowered position. Thus, an alert, signal or other alarms would begenerated to notify of the gate malfunction or incursion of a trainwithout a corresponding gate closure.

Finally, turning to FIG. 12C, the second, third, fourth and fifth areas312, 313, 314, 315 are more clearly visible, with the train exiting therail track crossing area 308, and detected in the crossing exit area316.

It is to be understood that while certain forms of the present inventionhave been illustrated and described herein, it is not to be limited tothe specific forms or arrangement of parts described and shown. Itshould be further understood that with various areas defined within thefield of interest that the system of the present invention can detectvarious objects, movement of objects, and positions of objects withinthose areas to determine unsafe conditions such as incursion of objectsinto the rail crossing region and to generate alerts or warnings inresponse. In addition, the system can similarly provide reports, alerts,and the like to confirm that the system is operating normally or asexpected.

What is claimed and desired to be secured by Letters Patent is asfollows:
 1. A system for railroad right-of-way occupancy detection,comprising: one or more LIDAR sensors operable to detect one or moreobjects of interest in a field of interest; and logic and controlcircuitry in communication with the LIDAR sensors, wherein the logic andcontrol circuitry is operable to determine information associated withthe one or more detected objects within the field of interest.
 2. Thesystem of claim 1, wherein the field of interest comprises one or moreareas of interest.
 3. The system of claim 2, wherein the fields of viewof the one or more LIDAR sensors overlap with the one or more areas ofinterest.
 4. The system of claim 1, wherein the field of interestcomprises an at-grade crossing, a station, a platform, a bridge, atunnel, other railroad right-of-way area, area adjacent to a railroadright-of-way area, and combinations thereof.
 5. The system of claim 1,wherein the information associated with the one or more detected objectscomprises behaviors of interest.
 6. The system of claim 5, whereinbehaviors of interest comprises velocity, direction, location, duration,and combinations thereof.
 7. The system of claim 1, wherein the logicand control circuitry is further operable to generate alerts, generatenotifications, generate an event log, and combinations thereof upondetection of an object.
 8. The system of claim 1, wherein the logic andcontrol circuitry is configured to detect a crossing gate malfunction.9. The system of claim 1, wherein the logic and control circuitry isconfigured to detect a vehicle incursion into the field of interest. 10.The system of claim 1, wherein the logic and control circuitry isconfigured to detect an object entering and/or exiting the field ofinterest.
 11. The system of claim 1, wherein the logic and controlcircuitry is configured to detect a near-miss of a train with an object.12. The system of claim 1, wherein the logic and control circuitry isconfigured to detect a collision of a train with an object.
 13. Thesystem of claim 1, wherein the logic and control circuitry is configuredto detect loitering of an object within the field of interest.
 14. Thesystem of claim 1, wherein the logic and control circuitry is configuredto detect a suspicious object within the field of interest.
 15. A methodof railroad right-of-way occupancy detection, comprising: providing oneor more LIDAR sensors operable to detect one or more objects of interestin a field of interest; and providing logic and control circuitry incommunication with the LIDAR sensors, wherein the logic and controlcircuitry is operable to determine information associated with the oneor more detected objects within the field of interest.
 16. The method ofclaim 15, wherein the field of interest comprises one or more areas ofinterest.
 17. The method of claim 16, wherein the fields of view of theone or more LIDAR sensors are arranged to overlap with the one or moreareas of interest.
 18. The method of claim 16, wherein the field ofinterest comprises an at-grade crossing, a station, a platform, abridge, a tunnel, or other railroad right-of-way.
 19. The method ofclaim 15, wherein the information associated with the one or moredetected objects comprises behaviors of interest.